Turn Hacker News comments into AI-summarized insight themes

The system groups similar comments from an online community and has AI summarize the common opinions in each group.

How the work actually flows

A straight line. Runs once per each comment.

Pattern: Sequence (1) ยท Multiple Instances with a priori Run-Time Knowledge (14)

flowchart TD trig(("user runs the analysis")):::human s0[("pull community comments")]:::store s1[["embed and cluster comments"]]:::mi s2["summarize each cluster"]:::svc s3[("save themes to spreadsheet")]:::store trig --> s0 s0 -->|"one per each comment"| s1 s1 --> s2 s2 --> s3 out[/"grouped comment themes with summaries"/]:::out pay{{"understand community sentiment at a glance"}}:::pay s3 --> out out --> pay classDef task fill:#e7f6fe,stroke:#34b8f0,color:#2c2a29 classDef svc fill:#f6f8fa,stroke:#7c8795,color:#2c2a29 classDef mi fill:#e7f6fe,stroke:#0079a8,color:#2c2a29,stroke-width:2px classDef human fill:#fff,stroke:#0079a8,color:#0079a8 classDef store fill:#f6f8fa,stroke:#0079a8,color:#2c2a29 classDef trig fill:#00a4eb,stroke:#0079a8,color:#fff,font-weight:bold classDef trigtime fill:#00a4eb,stroke:#0079a8,color:#fff,font-weight:bold classDef trigdata fill:#8ad4f5,stroke:#0079a8,color:#06314c,font-weight:bold classDef gate fill:#fff,stroke:#e8a23d,color:#6b4708,font-weight:bold classDef out fill:#1f9d6b,stroke:#167a53,color:#fff,font-weight:bold classDef pay fill:#06314c,stroke:#021f33,color:#fff
An outside serviceRuns once per itemA personA record or sheetResultPayoff
Build size
Advanced

A larger build with multiple systems, AI reasoning, and custom rules.

Business functions
AI Agents & Autonomous SystemsKnowledge Base & RAGSpreadsheet & Database OpsReporting & AnalyticsResearch & Market IntelligenceSurvey & Feedback
Connects
Google SheetsOpenAIQdrant

The problem it solves

You want to know what your community really thinks about a topic, but reading through hundreds of comments one by one takes hours. Patterns and repeated complaints or praise get lost in the volume, so you end up guessing instead of knowing.

Who it fits

A researcher, community manager, or product team trying to understand what people are saying about a topic across a large comment thread.

How it works

  1. Comments are pulled in from the online community
  2. Each comment is converted into an AI embedding and stored so similar comments can be found
  3. A clustering step groups comments that share similar themes
  4. AI reads each group and writes a summary of what people are saying, both positive and negative
  5. The insights and original comments are saved to a spreadsheet for review
What you get

Themes across comments you never had to read one by one

You get grouped themes and summaries of what people are really saying across thousands of comments, positive and negative alike.

What you get

A spreadsheet of grouped comment themes with an AI-written summary of the consensus in each group.

What you need

A vector database account, an OpenAI account, and a Google Sheets account.

We can build this. But should you?

The hard question is not how to build it. It is whether this is the right thing to build first.

That is what a Fractional Chief AI Officer figures out with you, before anyone writes a line of code.

Let's Talk Strategy

Related automations

Automatically cluster survey responses and surface key themes

Groups open-ended survey answers by meaning and has AI summarize the common themes in each group.

Advanced

Cluster customer reviews into themes with AI

Automatically groups customer reviews by theme and has AI summarize what customers love and hate.

Advanced

Draft LinkedIn posts from trending AI news for your approval

The system finds trending AI news, drafts a LinkedIn post in your voice, and emails it to you for approval.

Advanced

Turn your documents into a searchable AI knowledge assistant

Upload PDFs, images, or web links and get an AI chatbot that answers questions only from your own documents.

Advanced
Back to the AI Playbook